Finance - Accounting Seminars

 

 

Truth-telling is essential to efficient allocation of resources but is often undermined by strategic misreporting. We show how verifiably fair randomness, complemented by other blockchain functionalities, can lead to truth-telling at the cost of introduction of random noise in information transmission. The optimal trade-off between truthfulness and precision yields equilibria that outperform those attainable without randomization in information transmission. We characterize two classes of information equilibria: information designated to directly trigger value transfer via decentralized consensus (“enforcive information”), and strategic information sharing between Bayesian-rational decision makers (“advisive information”). Our findings demonstrate usefulness of randomized transmission in broad financial settings and illustrate the benefits of blockchain technology for optimal mechanism design.

Using a simple model of firm borrowing with standard ingredients, we show that commonly used empirical approaches in the literature do not recover the impact of credit supply shocks on loan-level lending, on total firm-level borrowing or on real outcomes. We propose new estimators that recover these effects. We apply our methodology to the 2011 credit crisis in Spain and show that it implies significantly smaller effects of loan supply shocks than those generated by current empirical approaches.

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Transaction Fee Mechanisms Robust to Welfare-Increasing Collusion

Barriers to Collusion-resistant Transaction Fee Mechanisms

 

 

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